Sampling Designs

Roberto Benedetti, Federica Piersimoni and Paolo Postiglione ()
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Roberto Benedetti: “G. d’Annunzio” University of Chieti-Pescara
Federica Piersimoni: Italian National Statistical Institute, ISTAT

Chapter Chapter 6 in Sampling Spatial Units for Agricultural Surveys, 2015, pp 103-147 from Springer

Abstract: Abstract The sample design is the most important stage of a survey, because any deficiencies cannot generally be compensated for during data editing and analysis. The classical designs for selecting random samples such as simple random sampling, stratification, and multistage cluster sampling were all developed to minimize the survey cost, while controlling the uncertainty associated with the estimates. Each scheme has advantages and disadvantages, but generally a combination can achieve stable and acceptable results in any field of statistical research. In this chapter, we review the main basic sampling designs.

Keywords: Auxiliary Variable; Simple Random Sampling; Statistical Unit; Inclusion Probability; Adaptive Cluster Sampling (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/978-3-662-46008-5_6

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